Towards effective person search with deep learning: A survey from systematic perspective
Person search detects and retrieves simultaneously a query person across uncropped
scene images captured by multiple non-overlapping cameras. In light of the deep learning …
scene images captured by multiple non-overlapping cameras. In light of the deep learning …
Joint discriminative representation learning for end-to-end person search
Person search simultaneously detects and retrieves a query person from uncropped scene
images. Existing methods are either two-step or end-to-end. The former employs two …
images. Existing methods are either two-step or end-to-end. The former employs two …
Domain adaptive person search via GAN-based scene synthesis for cross-scene videos
H Wang, T Cui, M Yao, H Pang, Y Du - Image and Vision Computing, 2023 - Elsevier
Person search has recently been a challenging task in the computer vision domain, which
aims to search specific pedestrians from real cameras. Nevertheless, most surveillance …
aims to search specific pedestrians from real cameras. Nevertheless, most surveillance …
Attentive multi-granularity perception network for person search
Person search is an extremely challenging task that seeks to identify individuals through
joint person detection and person re-identification from uncropped real scene images …
joint person detection and person re-identification from uncropped real scene images …
Deep intra-image contrastive learning for weakly supervised one-step person search
Weakly supervised person search aims to perform joint pedestrian detection and re-
identification (re-id) with only bounding-box annotations. Recently, the idea of contrastive …
identification (re-id) with only bounding-box annotations. Recently, the idea of contrastive …
Collaborative contrastive refining for weakly supervised person search
Weakly supervised person search involves training a model with only bounding box
annotations, without human-annotated identities. Clustering algorithms are commonly used …
annotations, without human-annotated identities. Clustering algorithms are commonly used …
Learning adaptive shift and task decoupling for discriminative one-step person search
Mainstream person search models aim to jointly optimize person detection and re-
identification (ReID) in a one-step manner. Despite notable progress, existing one-step …
identification (ReID) in a one-step manner. Despite notable progress, existing one-step …
Sat: Scale-augmented transformer for person search
Person search is a challenging computer vision problem where the objective is to
simultaneously detect and reidentify a target person from the gallery of whole scene images …
simultaneously detect and reidentify a target person from the gallery of whole scene images …
Context-aware feature learning for noise robust person search
Person search aims to localize and identify specific pedestrians from numerous surveillance
scene images. In this work, we focus on the noise in person search. We categorize the noise …
scene images. In this work, we focus on the noise in person search. We categorize the noise …
Face and body-shape integration model for cloth-changing person re-identification
O Agbodike, W Zhang, J Chen, L Wang - Image and Vision Computing, 2023 - Elsevier
Among the existing deep learning-based person re-identification (ReID) methods, human
parsing based on semantic segmentation is the most promising solution for ReID because …
parsing based on semantic segmentation is the most promising solution for ReID because …